1887

Chapter 17 : Issues of Study Design and Statistical Analysis for Environmental Microbiology

MyBook is a cheap paperback edition of the original book and will be sold at uniform, low price.

Preview this chapter:
Zoom in
Zoomout

Issues of Study Design and Statistical Analysis for Environmental Microbiology, Page 1 of 2

| /docserver/preview/fulltext/10.1128/9781555815882/9781555813796_Chap17-1.gif /docserver/preview/fulltext/10.1128/9781555815882/9781555813796_Chap17-2.gif

Abstract:

The practice of good science requires a concise description of study objectives and a study design that matches its objectives. A good study design requires (i) definition of the population or factors of interest in the study, (ii) identification of study units, (iii) collection of representative measurements, and (iv) a statistical analysis matched to study objectives and data characteristics. The goal of this chapter is to help one see the statistical issues involved in study design and data analysis. The majority of studies in environmental microbiology involve some form of comparisons since it is through comparisons that we learn where differences exist and/or what factors can influence microbial populations. Experimental designs specify the nature and extent of comparisons that are of interest in a particular study. The goal of data collection, be it in a sampling study or an experimental design, is to obtain a set of measures from a population to gain insight into how values for a particular population characteristic vary from sample unit to sample unit. In this chapter the authors have attempted to raise readers awareness of the role and function of statistics at both the study design and the data analysis steps of environmental microbiological studies.

Citation: Portier K, Corstanje R. 2007. Issues of Study Design and Statistical Analysis for Environmental Microbiology, p 199-215. In Hurst C, Crawford R, Garland J, Lipson D, Mills A, Stetzenbach L (ed), Manual of Environmental Microbiology, Third Edition. ASM Press, Washington, DC. doi: 10.1128/9781555815882.ch17

Key Concept Ranking

Microbial Communities in Environment
0.644309
Environmental Microbiology
0.6140351
Soil Microbial Communities
0.45601654
0.644309
Highlighted Text: Show | Hide
Loading full text...

Full text loading...

Figures

Image of FIGURE 1
FIGURE 1

Spatial sampling plans, each containing 40 locations. (a) Simple random locations; (b) random locations within cells of a systematic grid (spatial stratification); (c) systematic locations with a random starting point and fixed between-sample distance, δ; and (d) overlapping grid samples of equal between-sample distance and two random starting points.

Citation: Portier K, Corstanje R. 2007. Issues of Study Design and Statistical Analysis for Environmental Microbiology, p 199-215. In Hurst C, Crawford R, Garland J, Lipson D, Mills A, Stetzenbach L (ed), Manual of Environmental Microbiology, Third Edition. ASM Press, Washington, DC. doi: 10.1128/9781555815882.ch17
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of FIGURE 2
FIGURE 2

Typical shapes for common discrete statistical distributions. Distribution parameters: n, number of experiments, ranging from 2 to infinity; π, probability of success, ranging between 0 and 1; λ > 0, Poisson mean.

Citation: Portier K, Corstanje R. 2007. Issues of Study Design and Statistical Analysis for Environmental Microbiology, p 199-215. In Hurst C, Crawford R, Garland J, Lipson D, Mills A, Stetzenbach L (ed), Manual of Environmental Microbiology, Third Edition. ASM Press, Washington, DC. doi: 10.1128/9781555815882.ch17
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of FIGURE 3
FIGURE 3

Typical shapes for common continuous statistical distributions. Distribution parameters are displayed as Greek letters. For the normal and lognormal distributions, µ and σ are the mean and standard deviation controlling the center and spread, respectively. The Weilbull distribution is controlled by a shape and a scale parameter. The Student F, and chi-square distributions are controlled by one or two parameters referred to as the degrees of freedom, 1 ≤ df, df1, df2 < infinity. For these distributions, changing the degrees of freedom changes both the shape and spread of the distribution as demonstrated by the dotted lines.

Citation: Portier K, Corstanje R. 2007. Issues of Study Design and Statistical Analysis for Environmental Microbiology, p 199-215. In Hurst C, Crawford R, Garland J, Lipson D, Mills A, Stetzenbach L (ed), Manual of Environmental Microbiology, Third Edition. ASM Press, Washington, DC. doi: 10.1128/9781555815882.ch17
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of FIGURE 4
FIGURE 4

Examples of normal quantile plots. Closeness to the straight line is a measure of the normality of the sample data.

Citation: Portier K, Corstanje R. 2007. Issues of Study Design and Statistical Analysis for Environmental Microbiology, p 199-215. In Hurst C, Crawford R, Garland J, Lipson D, Mills A, Stetzenbach L (ed), Manual of Environmental Microbiology, Third Edition. ASM Press, Washington, DC. doi: 10.1128/9781555815882.ch17
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of Untitled
Untitled

Citation: Portier K, Corstanje R. 2007. Issues of Study Design and Statistical Analysis for Environmental Microbiology, p 199-215. In Hurst C, Crawford R, Garland J, Lipson D, Mills A, Stetzenbach L (ed), Manual of Environmental Microbiology, Third Edition. ASM Press, Washington, DC. doi: 10.1128/9781555815882.ch17
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of FIGURE 5
FIGURE 5

Frequency and density histograms for normally distributed data. Note that the shapes of the distribution are similar and only the vertical axis scale is changed.

Citation: Portier K, Corstanje R. 2007. Issues of Study Design and Statistical Analysis for Environmental Microbiology, p 199-215. In Hurst C, Crawford R, Garland J, Lipson D, Mills A, Stetzenbach L (ed), Manual of Environmental Microbiology, Third Edition. ASM Press, Washington, DC. doi: 10.1128/9781555815882.ch17
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of FIGURE 6
FIGURE 6

Comparative box plots indicating the median (middle of notch), upper and lower quartiles (solid box top and bottom), interquartile range (IQR = height of box), upper and lower fence values (line terminators = median ± 3 IQR), and potential outliers (circle dots).

Citation: Portier K, Corstanje R. 2007. Issues of Study Design and Statistical Analysis for Environmental Microbiology, p 199-215. In Hurst C, Crawford R, Garland J, Lipson D, Mills A, Stetzenbach L (ed), Manual of Environmental Microbiology, Third Edition. ASM Press, Washington, DC. doi: 10.1128/9781555815882.ch17
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of FIGURE 7
FIGURE 7

Biplot of the first two principal components of a 4-variate analysis which is known to have three groups, identified as A, B, and C.

Citation: Portier K, Corstanje R. 2007. Issues of Study Design and Statistical Analysis for Environmental Microbiology, p 199-215. In Hurst C, Crawford R, Garland J, Lipson D, Mills A, Stetzenbach L (ed), Manual of Environmental Microbiology, Third Edition. ASM Press, Washington, DC. doi: 10.1128/9781555815882.ch17
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of Untitled
Untitled

Citation: Portier K, Corstanje R. 2007. Issues of Study Design and Statistical Analysis for Environmental Microbiology, p 199-215. In Hurst C, Crawford R, Garland J, Lipson D, Mills A, Stetzenbach L (ed), Manual of Environmental Microbiology, Third Edition. ASM Press, Washington, DC. doi: 10.1128/9781555815882.ch17
Permissions and Reprints Request Permissions
Download as Powerpoint

References

/content/book/10.1128/9781555815882.ch17
1. Becker, S.,, P. Böger,, R. Oehlmann, and, A. Ernst. 2000. PCR bias in ecological analysis: a case study for quantitative Taq nuclease assays in analyses of microbial communities. Appl. Environ. Microbiol. 66:49454953.
2. Chatterjee, S.,, and B. Price. 1977. Regression Analysis by Example. John Wiley & Sons, Inc., New York, N.Y.
3. Cressie, N. 1991. Statistics for Spatial Data. John Wiley & Sons, Inc., New York, N.Y.
4. Duda, R. O.,, P. E. Hart, and, D. G. Stork. 2001. Pattern Classification, 2nd ed. John Wiley & Sons, Inc., New York, N.Y.
5. Gardiner, W. P. 1997. Statistics for the Biosciences. Prentice-Hall, Inc., London, United Kingdom.
6. Gilbert, R. O. 1987. Statistical Methods for Environmental Pollution Monitoring. Van Nostrand Reinhold, New York, N.Y.
7. Dixon, P. M. 2001. The bootstrap and the jackknife; describing the precision of ecological indices, p. 267–288. In S. M. Scheiner and, J. Gurevitch (ed.), Design and Analysis of Ecological Experiments. Oxford University Press, Oxford, United Kingdom.
8. Evans, M.,, N. Hastings, and, B. Peacock. 2000. Statistical Distributions, 3rd ed. John Wiley & Sons, Inc., New York, N.Y.
9. Franklin, R. B.,, and A. L. Mills. 2003. Multiscale variation in spatial heterogeneity for microbial community structure in an eastern Virginia agricultural field. FEMS Microbiol. Ecol. 44:335346.
10. Friendly, M. 1994. Mosaic displays for multi-way contingency tables. J. Am. Stat. Assoc. 89:190200.
11. Hill, M. O. 1979. TWINSPAN—a FORTRAN Program for Arranging Multivariate Data in an Ordered Two-Way Table by Classification of the Individuals and Attributes. Ecology and Systematics, Cornell University, Ithaca, N.Y.
12. Hill, M. O.,, and H. G. Gauch. 1980. Detrended correspondence analysis: an improved ordination technique. Vegetatio 42:4758.
13. Hurlbert, S. H. 1984. Pseudoreplication and the design of ecological field experiments. Ecol. Monogr. 54:187211.
14. Joergensen, R. G.,, and S. Scheu. 1999. Response to soil microorganisms to the addition of carbon, nitrogen and phosphorus in a forest Rendzina. Soil Biol. Biochem. 31:859866.
15. Johnson, D. H. 1999. The insignificance of statistical significance testing. J. Wildl. Manag. 63:763772.
16. Johnson, R. A.,, and D. W. Wichern. 1989. Applied Multivariate Statistical Analysis, 2nd ed. Prentice-Hall, Inc., Englewood Cliffs, N.J.
17. Kingsolver, K. M.,, and D. G. Schemske. 1991. Analyzing selection with path analysis. Trends Ecol. Evol. 6:276280.
18. Krebs, C. J. 1999. Ecological Methodology, 2nd ed. Benjamin/Cummings, Menlo Park, Calif.
19. Krivtsov, V. 2004. Investigations of indirect relationships in ecology and environmental sciences: a review and the implications for comparative theoretical ecosystem analysis. Ecol. Model. 174:3754.
20. Laflaive, J.,, R. Cereghino,, M. Danger,, G. Lacroix, and, L. Ten-Hage. 2005. Assessment of self-organizing maps to analyze sole-carbon source utilization profiles. J. Microbiol. Methods 62:89102.
21. Legendre, P. 1993. Spatial autocorrelation: trouble or new paradigm? Ecology 74:16591673.
22. Legendre, P.,, and L. Legendre. 1998. Numerical Ecology, 2nd ed. Elsevier, Amsterdam, The Netherlands.
23. Levy, P. S.,, and S. Lemeshow. 1999. Sampling of Populations, Methods and Applications, 3rd ed. John Wiley & Sons, Inc., New York, N.Y.
24. Ludwig, J. A.,, and J. F. Reynolds. 1988. Statistical Ecology. John Wiley & Sons, Inc. New York, N.Y.
25. Magurran, A. E. 1988. Ecological Diversity and Measurement. Princeton University Press, Princeton, N.J.
26. Manley, B. F. J. 1994. Multivariate Statistical Methods: A Primer. Chapman & Hall/CRC Press, Boca Raton, Fla.
27. Manley, B. F. J. 1997. Randomization, Bootstrap and Monte Carlo Methods in Biology, 2nd ed. Chapman & Hall/CRC Press, Boca Raton, Fla.
28. McCune, B.,, J. B. Grace, and, D. L. Urban. 2002. Analysis of Ecological Communities. MjM Software Design, Gleneden Beach, Oreg.
29. Morris, S. J. 1991. Spatial distribution of fungal and bacterial biomass in southern Ohio hardwood forest soils: fine scale variability and microscale patterns. Soil Biol. Biochem. 31:13751386.
30. Ogram, A. 2000. Soil molecular microbial ecology at age 20: methodological challenges for the future. Soil Biol. Biochem. 32:14991504.
31. Palumbo, A. V.,, J. C. Schryver,, M. W. Fields,, C. E. Bagwell,, J. Z. Zhou,, T. Yan,, X. Liu, and, C. C. Brandt. 2004. Coupling of functional gene diversity and geochemical data from environmental samples, Appl. Environ. Microbiol. 70:65256534.
32. Pennanen, P.,, J. Liski,, E. Baath,, V. Kitunen,, J. Uotila,, C. J. Westman, and, H. Fritze. 1999. Structure of the microbial communities in coniferous forest soils in relation to site fertility and stand development stage. Microb. Ecol. 38:168179.
33. Reynoldson, T. B.,, R. H. Norris,, V. H. Resh,, K. E. Day, and, D. M. Rosenberg. 1997. The reference condition: a comparison of multimetric and multivariate approaches to assess water quality impairment using benthic macroinvertebrates. J. N. Am. Benthol. Soc. 16:833852.
34. Scheaffer, R. L.,, W. Mendenhall III, and, R. L. Ott. 1996. Elementary Survey Sampling, 5th ed. Duxbury Press/Wadsworth Publishing Co., Belmont, Calif.
35. Snedecor, G. W.,, and W. G. Cochran. 1989. Statistical Methods. Iowa State University Press, Ames.
36. Sokal, R. R.,, and F. J. Rohlf. 1995. Biometry, 3rd ed. W. H. Freeman, New York, N.Y.
37. Stewart-Oaten, A.,, and W. W. Murdoch. 1986. Environmental impact assessment: “pseudoreplication” in time. Ecology (Tempe) 67:929940.
38. Tabachnik, B. G.,, and L. S. Fidell. Using Multivariate Statistics, 4th ed. Allyn & Bacon, Boston, Mass.
39. Ter Braak, C. J. F. 1986. Canonical correspondence analysis: a new eigenvector technique for multivariate direct gradient analysis. Ecology 67:11671179.
40. Thode, H. C., Jr. 2002. Testing for Normality. Marcel Dekker, Inc., New York, N.Y.
41. Thompson, S. K. 2002. Sampling, 2nd ed. John Wiley & Sons, Inc., New York, N.Y.
42. Verbeke, G.,, and G. Molenberghs. 2000. Linear Mixed Models for Longitudinal Data. Springer-Verlag, New York, N.Y.
43. Webster, R.,, and M. A. Oliver. 2001. Geostatistics for Environmental Scientists. John Wiley & Sons, New York, N.Y.
44. Zar, J. H. 1996. Biostatistical Analysis, 3rd ed. Prentice-Hall, Inc., Upper Saddle River, N.J.

This is a required field
Please enter a valid email address
Please check the format of the address you have entered.
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error